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Fully Bayesian Estimation of Simultaneous Regression Quantiles under Asymmetric Laplace Distribution Specification

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  • Josephine Merhi Bleik

Abstract

In this paper, we are interested in estimating several quantiles simultaneously in a regression context via the Bayesian approach. Assuming that the error term has an asymmetric Laplace distribution and using the relation between two distinct quantiles of this distribution, we propose a simple fully Bayesian method that satisfies the noncrossing property of quantiles. For implementation, we use Metropolis-Hastings within Gibbs algorithm to sample unknown parameters from their full conditional distribution. The performance and the competitiveness of the underlying method with other alternatives are shown in simulated examples.

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  • Josephine Merhi Bleik, 2019. "Fully Bayesian Estimation of Simultaneous Regression Quantiles under Asymmetric Laplace Distribution Specification," Journal of Probability and Statistics, Hindawi, vol. 2019, pages 1-12, June.
    • Handle: RePEc:hin:jnljps:8610723
    DOI: 10.1155/2019/8610723
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    Cited by:

    1. Mani Suleiman & Haydar Demirhan & Leanne Boyd & Federico Girosi & Vural Aksakalli, 2022. "Bayesian prediction of emergency department wait time," Health Care Management Science, Springer, vol. 25(2), pages 275-290, June.

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